In: Statistics and Probability
Solve for the predicted values of y and the residuals
for the following data.
| x | 12 | 21 | 28 | 8 | 20 | 
| y | 17 | 15 | 22 | 19 | 24 | 
Do not round the intermediate values. (Round your
answers to 3 decimal places.)
| x | y | Predicted (ŷ) | Residuals (y-ŷ) | 
| 12 | 17 | ||
| 21 | 15 | ||
| 28 | 22 | ||
| 8 | 19 | ||
| 20 | 24 | 
The following data are passed:
| X | Y | 
| 12 | 17 | 
| 21 | 15 | 
| 28 | 22 | 
| 8 | 19 | 
| 20 | 24 | 
The independent variable is X, and the dependent variable is Y. In order to compute the regression coefficients, the following table needs to be used:
| X | Y | X*Y | X2 | Y2 | |
| 12 | 17 | 204 | 144 | 289 | |
| 21 | 15 | 315 | 441 | 225 | |
| 28 | 22 | 616 | 784 | 484 | |
| 8 | 19 | 152 | 64 | 361 | |
| 20 | 24 | 480 | 400 | 576 | |
| Sum = | 89 | 97 | 1767 | 1833 | 1935 | 
Based on the above table, the following is calculated:





Therefore, based on the above calculations, the regression coefficients (the slope m, and the y-intercept n) are obtained as follows


Therefore, we find that the regression equation is:
Y = 16.5096 + 0.1624 X
| x | y | Predicted (ŷ) | Residuals (y-ŷ) | 
| 12 | 17 | 18.4584 | -1.4584 | 
| 21 | 15 | 19.92 | -4.92 | 
| 28 | 22 | 21.0568 | 0.9432 | 
| 8 | 19 | 17.8088 | 1.1912 | 
| 20 | 24 | 19.7576 | 4.2424 |